As computing technology advances and computing devices become more prevalent, the usage of computers for daily activities has become commonplace for both personal and business reasons. To keep up with demand, data collection has grown exponentially. The purpose of data collection, and later processing of the data, is to understand the meaning of the collected data and assemble the gathered data for a useful purpose.
A problem associated with the accumulation of data, and any corresponding usage of the data, is errors contained within the data (e.g., low quality data). Examples of errors can include incorrect data, missing data, typographical errors, misplaced data, duplicates, as well as other problems. People and business that rely on data that contains errors can base decisions, analysis, and/or other actions on the data and, if the data is flawed, the resulting decisions, analysis, and so on, can also be flawed. If the errors are discovered after the fact, confidence and related trust in the data can be compromised. In some cases, if the data does not meet a sufficient quality level, the data might not be relied upon.
Some systems utilize a generic approach to improving data quality. The generic approach is based on a “one-size fits all” mentality. For example, the generic approach applies generic algorithms to the data in an attempt to cleanse or improve the quality of the data. Since generic algorithms are applied regardless of the data contents, the generic approaches can only provide limited solutions. In some cases, the generic approach might not be able to solve the problems associated with the data. Thus, the data that has been cleansed with the generic algorithms can still be of low quality since the original problem might not have been addressed.
The above-described deficiencies of today's computing systems and data quality solutions are merely intended to provide an overview of some of the problems of conventional systems, and are not intended to be exhaustive. Other problems with conventional systems and corresponding benefits of the various non-limiting embodiments described herein may become further apparent upon review of the following description.